About a billion people every month, who between them conduct about a billion searches every day, use Google Maps. It is now so ubiquitous, such a vital part of so many of our lives, that it feels odd to think it didn’t exist until 2005. Of all of the search giant’s many tentacles reaching octopus-like into every area of our existence, Maps, together with its partner Google Earth and their various offspring, can probably claim to be the one that has changed our day-to-day life the most.
It might not yet be obvious, but it’s as good a model for business AI as any.
For most people, how Google Maps works is not understood. From their perspective, the application just works and, like any good Augmented Intelligence application, that’s how it should be. But a tremendous amount of innovation and investment has gone into making the complex task of providing directions from one location to another so simple to use. It is a wonderful example of how humans have poured oceans of knowledge into a system to make other humans more productive. The maps we used to keep folded in the glove compartments of our cars were a collection of lines and shapes that we overlaid with human intelligence. Now, as we’ve seen, a map is a collection of lines and shapes with embedded knowledge and intelligence.
Behind every Google Map, there is a much more complex map that’s the key to your queries but hidden from your view. The deep map contains the logic of places: their no-left-turns and freeway on-ramps, speed limits and traffic conditions. Google, which began as a search company, figured out that, as the mobile world exploded, where you were searching from became as important as what you’re searching for.
Google Maps began as a desktop program designed by Where2 Technologies. In October 2004, Where2 was acquired by Google and together they converted it to a web application. Where2 was a tiny startup based in Australia that almost went bust before the Google deal. Just before Where2 expected to finalize an agreement with Sequoia Capital, Sequoia dropped funding discussions with them when Yahoo Maps launched an update that added Yellow Pages entries on a map.
Through a series of other acquisitions and licensing agreements Google added a host of knowledge sources to the maps. Notable acquisitions were Keyhole, a geospatial visualization company, and Zipdash, a company that provided real-time traffic analysis. Zipdash was a lot like Waze, a company that Google acquired in 2013 for $1 billion (a lot more than the $2 million that CEO Mark Crady received for Zipdash). Mapping data from Tele Atlas, a Netherlands-based mapping company, and a host of other data services were also included.
In 2007, TomTom bought Tele Atlas and Nokia bought Navteq, and so Google initiated a project—called Ground Truth—to control its own map data. A team of 20 people across the world worked full-time on acquiring map data. Megan Quinn (now General Partner at Spark Capital), who led the data acquisition project, sent out an email to every Google employee asking them to find inaccuracies or bugs in the maps for their home towns, promising them a home-made cookie for every bug they found. Quinn ended up baking 7,000 chocolate-chip cookies. This was a critical wave of human input to Google Maps.
The sheer amount of human effort that goes into Google’s maps is just mind-boggling. Google understands that the best way to figure out if you can make a left turn at a particular intersection is still to have a person look at a sign—whether that’s a human driving or a human looking at an image generated by a Street View car. Humans are coding every bit of the logic of the road onto a representation of the world so that computers can simply duplicate (infinitely, instantly) the judgments that a person already made.
Knowledge, Data, Context, Reasoning, and Notifications
Next time that you are standing on the sidewalk in Manhattan looking for directions to your meeting on the Upper East Side, sitting in your car in Sausalito thinking about a trip to Monterey, or if you are a little more adventurous, planning to explore the Angkor Wat UNESCO world heritage site in Cambodia, or heading out from Helsinki on a trek to see the Northern Lights from Pitkäjärvi Lake in Finland, you can use Google Maps to plot your course. It’s all because Google has made the investment to infuse Maps with a ginormous foundation of knowledge, much of it collected through automation, but quite a bit of it augmented by human input and ingenuity.
Google Maps is the most wonderful example of an Augmented Intelligence application. We all understand it. Although the task of mapping the world is on a scale that dwarfs any business application, Maps clearly contains all of the components that should be on your list if you are building an augmented application for knowledge workers.
I split my time between traveling in the United States and living in Cork in Ireland. I am a very keen, but very bad and infrequent, golfer. When I have American visitors to my home in Cork, I recommend taking a trip to Waterville Golf Club in the extreme South West of Ireland. Even if you are not a golfer, the trip to Waterville is stunningly beautiful and shows off the best of Ireland, particularly when it is not raining. When I can I drive my guests to Waterville myself, but if I don’t have the time, I just use my iPhone to show them how to find this gem of a destination for themselves. Using all of the Augmented Intelligence capabilities in Google Maps my friends can confidently head off on their trip.
It starts with Knowledge. Because Google has effectively mapped the world, it has a foundation of knowledge with which it can work to build the journey plan. Then we key in Data: our chosen destination ‘Waterville Golf Links.’ As Google Maps has geo-location services built in, it does not need to be told the starting location. It has the Context. Now it begins its Reasoning. Because I live in a neighborhood that has only one way out to the main road, it tells us to make a U-turn if the car is facing the wrong direction. As we are in Ireland, Google knows that we should drive on the left-hand side of the road and when we encounter a roundabout it knows that we should navigate it in a clockwise direction.
As you can see from the map, the trip takes a little over two and a half hours. Along the way, as the location or Context changes, the user is continuously receiving Notifications, pushing information to the driver in plenty of time for the driver to know the next action to take: “In 500m, at the roundabout take the second exit and continue on the R641”.
How Google Maps works provides us with a blueprint for Augmented Intelligence applications in business. Knowledge, Data, Context, and Reasoning are critical components of these or any Augmented Intelligence applications for knowledge workers. Where updates occur in any of Knowledge, Data, or Context, then Notifications are needed to keep the user in the loop on anything that might impact the situation.
Augmented Intelligence applications need to have knowledge of the core concepts of the specific domain to which the application is being applied. Experienced practitioners and domain experts know the ‘How to,’ the ‘Best way,’ the proven approaches to solving the problem and getting to a specific solution destination. Making that available to someone who is making that journey for the first time by providing signposts—effectively a map of the journey—means it is less likely that they will take a wrong turn. Knowledge on its own is not enough; Data and Context are necessary. Without Context, it is really hard to apply the knowledge and, without Data, you don’t know the specific problem you are trying to solve.
Augmented Intelligence applications make the journey of knowledge workers more frictionless, and make it easier for less experienced workers to add more value to their companies and to get more satisfaction from the work that they do. It starts one journey at time and gets more valuable with each human interaction to uncover new destinations and greater possibilities.
Without Google Maps, or similar technology, autonomous cars would not be possible. We wouldn’t have Uber, or Lyft, or any other service that depends on geo-location services, and we would still be struggling to fold up the paper map to fit it back into the glove compartment in our cars. Those days are better left behind.
This is an extract from my latest book: TOMORROW | TODAY: How AI Impacts How We Work, Live, and Think (and it’s not what you expect)
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Donal Daly is Executive Chairman of Altify having founded the company in 2005. He is author of numerous books and ebooks including the Amazon #1 Best-sellers Account Planning in Salesforce and Tomorrow | Today: How AI Impacts How We Work, Live, and Think. Altify is Donal’s fifth global business enterprise.